The present technology relates to an information processing apparatus, an information processing method, and a program, and, particularly to an information processing apparatus, an information processing method, and a program, enabling an agent such as a robot capable of performing various actions to easily perform learning of objects or the like in an environment in which the actions are performed.
For example, in a case where an agent capable of performing actions performs an object moving task in which the agent moves a body which is an object such as the hand of the agent which can be moved by the agent itself and thereby moves a non-body which is an object other than the body of the agent without prior knowledge by using captured images of the environment in which the agent is placed, it is necessary for the agent to recognize the hand in the image as in the hand regard performed by an infant.
For example, in “Harumitsu NOBUTA, Shun NISHIDE, Tetsuya OGATA, Hiroshi G. OKUNO, “Acquisition of Spatial Map based on Body Schema Using Neurodynamical Model”, THE 29TH ANNUAL CONFERENCE OF THE ROBOTICS SOCIETY OF JAPAN”, a method has been proposed in which an MTRNN (Multiple Timescale Recurrent Neural Network) for acquiring a body schema as an internal model is employed, and an agent identifies a body of the agent among a plurality of objects including the body of the agent by using the MTRNN.
In “Harumitsu NOBUTA, Shun NISHIDE, Tetsuya OGATA, Hiroshi G. OKUNO, “Acquisition of Spatial Map based on Body Schema Using Neurodynamical Model”, THE 29TH ANNUAL CONFERENCE OF THE ROBOTICS SOCIETY OF JAPAN”, a movement command issued for moving the body by the agent, and position information in an environment of three objects including one object which is the body of the agent which is moved in response to the movement command and two objects which are non-bodies, are given to the MTRNN, and then the MTRNN is learned.
In addition, in “Harumitsu NOBUTA, Shun NISHIDE, Tetsuya OGATA, Hiroshi G. OKUNO, “Acquisition of Spatial Map based on Body Schema Using Neurodynamical Model”, THE 29TH ANNUAL CONFERENCE OF THE ROBOTICS SOCIETY OF JAPAN”, only a movement command is given to the MTRNN after being learned, and the movement command is recognized. Thereafter, in “Harumitsu NOBUTA, Shun NISHIDE, Tetsuya OGATA, Hiroshi G. OKUNO, “Acquisition of Spatial Map based on Body Schema Using Neurodynamical Model”, THE 29TH ANNUAL CONFERENCE OF THE ROBOTICS SOCIETY OF JAPAN″, prediction values of the position information of the three objects are obtained (generated) using the recognition result of the movement command from the MTRNN, and position information of the body of the agent (and position information of the non-bodies) are specified from the position information of the three objects on the basis of prediction errors of the prediction values. Further, an object moved along positions indicated by the position information is identified as the body of the agent.